基于多原理的机场旅客吞吐量预测研究

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Research on Airport Passenger Throughput Forecasting Based on Multiple Principles ， LIU Wenzheng，WANGRongjuan，YUAN Jianle，LYU Xinyang （AirportSchool，ShandongUniversityofAeronautics，Binzhou 2566oo，China）

关键词：机场旅客吞吐量；趋势外推模型；多元线性回归模型；灰色预测模型；组合预测模型中图分类号：F562；V354 文献标志码：A DOI： 10.13714/j.cnki.1002-3100.2025.18.027

Abstract：Efectivepassngerthroughutforecastingplaysapivotaloleinptimsingresoucealocationandimprovinserviceuality inairports.Iiserohabstoidrstigodelteatigtrdapolaiodeluile regresiomodeladtrasaioalgeyforeastingodel，tefrecastingprinciple，elytetredseatiosipetweetaad time，thelawexistinginthedataitelf，andthetrendsrelationshipetweendataandotherfactorsexcepttime，arecombined，adthe passnger throughputofanairportfrom2010—2019 isusedasthesampledatatotestthecombined model.Theresultsshowthatthe absolute value of the prediction error of the combined model are less than 1.72% ，indictingthecombined model canbeused to predict the pasengerthroughputinfutureyearsforits highaccracyByusingthecombinedforecasting model topredictthepasengerthroughput of thairportduringtheperiodof242035，iis kownthattegowthateoftheairport'spasengerthroughputisdecrsingyear by year， with an average growth rate of 5.84% ，and the passenger throughput in 2035 will reach 89.115 2 million，which is 1.99 times the pasenger throughput in 2O19. The research provides theoretical support forthe passenger throughput forecast in airports.

Key words：arprtpassngerthrougut; trendextralatioodel;utipleliearregessonmodel;grapredictnmodel;oined forecasting model

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